Iterative technique for the synthesis of optical-correlation filters

Optical-correlation filters that are translationally and rotationally invariant are made target specific by incorporating all the angular harmonics of the target image. An iterative design method similar to the technique of convex projections allows the image angular harmonics to be rephased so that the filter exhibits a constant-amplitude rotational response. Rotating this filter in the Fourier plane forms the Fourier summation of all angular harmonics of the input image. Ari image to be detected must have angular-harmonic terms that have an amplitude and a phase that are keyed exactly to the target image. This lock-and-tumbler filter exhibits excellent discrimination capability while preserving rotational invariance.

[1]  A W Lohmann,et al.  Optical character recognition based on nonredundant correlation measurements. , 1979, Applied optics.

[2]  H H Arsenault,et al.  Optical pattern recognition using circular harmonic expansion. , 1982, Applied optics.

[3]  N. C. Gallagher,et al.  Method for Computing Kinoforms that Reduces Image Reconstruction Error. , 1973, Applied optics.

[4]  Donald W. Sweeney,et al.  Rotationally invariant correlation filtering , 1985 .

[5]  D. Youla,et al.  Image Restoration by the Method of Convex Projections: Part 1ߞTheory , 1982, IEEE Transactions on Medical Imaging.

[6]  A. Papoulis.  A new algorithm in spectral analysis and band-limited extrapolation. , 1975 .

[7]  H J Caulfield,et al.  Improved discrimination in optical character recognition. , 1969, Applied optics.

[8]  H H Arsenault,et al.  Pattern discrimination by multiple circular harmonic components. , 1984, Applied optics.

[9]  A. B. Vander Lugt,et al.  Signal detection by complex spatial filtering , 1964, IEEE Trans. Inf. Theory.

[10]  R. Gerchberg.  A practical algorithm for the determination of phase from image and diffraction plane pictures , 1972 .

[11]  D Casasent,et al.  Multivariant technique for multiclass pattern recognition. , 1980, Applied optics.

[12]  H H Arsenault,et al.  Rotation-invariant digital pattern recognition using circular harmonic expansion. , 1982, Applied optics.

[13]  Demetri Psaltis,et al.  V Deformation Invariant, Space-Variant Optical Pattern Recognition , 1978 .

[14]  H Stark,et al.  Rotation-invariant pattern recognition using a vector reference , 1984 .

[15]  Henri H. Arsenault,et al.  Rotation-Invariant Pattern Recognition , 1984 .

[16]  R. Gerchberg.  Super-resolution through Error Energy Reduction , 1974 .

[17]  D Casasent,et al.  Unified synthetic discriminant function computational formulation. , 1984, Applied optics.

[18]  E. Paek,et al.  Discrimination enhancement in optical pattern recognition by using a modified matched filter , 1979 .

[19]  H J Caulfield.  Linear combination of filters for character recognition: a unified treatment. , 1980, Applied optics.